Now showing items 1-5 of 5
Bayesian compressive sensing for ultra-wideband channel estimation: algorithm and performance analysis
Due to the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to ...
Comparison of Compressed Sensing Based Algorithms for Sparse Signal Reconstruction
Compressed sensing theory shows that any signal which is defined as sparse in a given domain can be reconstructed using fewer linear projections instead of using all Nyquist-rate samples. In this paper we investigate basis ...
The Effect of Primary User Bandwidth on Bayesian Compressive Sensing Based Spectrum Sensing
The application of compressive sensing (CS) theory has found great interest in wideband spectrum sensing. Although most studies have considered perfect reconstruction of the primary user signal it is actually more important ...
Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing
In wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider ...
The Effect of Channel Models on Compressed Sensing Based UWB Channel Estimation
Ultra-wideband (UWB) multipath channels are assumed to have a sparse structure as the received consecutive pulses arrive with a considerable time delay and can be resolved individually at the receiver. Due to this sparse ...